class_docstr: Layer that can safely used in a tf.data pipeline.
  
  The `call()` method must solely rely on `self.backend` ops.
  
  Only supports a single input tensor argument.
code: def __init__(self, **kwargs):
      super().__init__(**kwargs)
      self.backend = backend_utils.DynamicBackend()
      self._allow_non_tensor_positional_args = True
  
file_path: keras/keras/layers/preprocessing/tf_data_layer.py
imports: import tree
  import keras.backend
  from keras.layers.layer import Layer
  from keras.random.seed_generator import SeedGenerator
  from keras.utils import backend_utils
  from keras.utils import tracking
label_desc: Use image node_id 1 to create a new TFDataLayer object from inherited base classes: Layer with example: obj = TFDataLayer()